I would like to clarify that this is not a soft advertisement from a self-media platform. This account is purely for personal study.

Thank you, Mr. Yuan, for helping coordinate and obtain a Manus test code, and also especially thank Xiao Hong for the arrangement. The overall testing experience was really great!

Analysis of per capita revenue contribution of the top 10 tech companies
Thought process

The process documents are also clearly visible.

My result:
Annual Revenue per Employee for Top 10 Tech Companies by Market Cap (2025)
Key Observations:
NVIDIA leads with the highest revenue per employee at $3.63 million, which is nearly 9 times higher than Amazon's figure.
Apple ranks second with $2.64 million revenue per employee despite having the highest market cap among all tech companies.
Amazon has the lowest revenue per employee at
638B) among the top 10 tech companies. Meta Platforms shows strong efficiency with the third-highest revenue per employee at $2.22 million.
Companies focused on semiconductor and hardware technology (NVIDIA, Apple, Broadcom, TSMC) generally show higher revenue per employee than software and service-oriented companies.
Amazon's low revenue per employee reflects its labor-intensive business model with a massive workforce of over 1.5 million employees.
Data Sources:
Market cap data from companiesmarketcap.com as of March 2025 Revenue and employee count data from stockanalysis.com as of March 2025 TSMC revenue converted from TWD to USD using approximate exchange rate All figures rounded to nearest whole number where appropriate
Travel plan for Tokyo in April
Thought process

Process document

My result:
Take a look at the table of contents first.
Tokyo Trip Guide - April 2025
Introduction
This comprehensive guide has been prepared for your Tokyo trip in April 2025. April is one of the most beautiful times to visit Tokyo, as it coincides with cherry blossom season, offering a magical atmosphere throughout the city. This guide covers everything you need to know about Tokyo's weather in April, must-visit attractions, cultural events (with special focus on cherry blossom festivals), and practical travel tips to help you make the most of your journey.
Table of Contents
Weather in April Popular Attractions Cherry Blossom Viewing & Cultural Events Travel Tips & Practical Information Suggested Itinerary Ideas
The following details:
Summary of YouTube videos
Thought process

Process documentation


The result for me:
Gen-AI Application Market Analysis
Thought Process

Process Documentation

My Results:Generative AI Landscape 2025
Overview
This visualization presents a comprehensive mapping of the generative AI ecosystem as of 2025, categorizing key players across the value chain from infrastructure to applications.
Market Context
The generative AI market has experienced explosive growth since the introduction of ChatGPT in late 2022, reaching approximately 89.9 billion and $1 trillion by 2030-2034. This landscape map organizes the most influential companies shaping this rapidly evolving space.
Infrastructure Layer
At the foundation of the generative AI ecosystem lies the infrastructure that powers model development and deployment.
Hardware Providers
NVIDIA (92% GPU market share) AMD Intel Google TPU
Cloud Service Providers
Microsoft Azure AWS Google Cloud Oracle Cloud
Data Storage & Processing
Snowflake Databricks MongoDB Pinecone Weaviate
Foundation Models & Development
Full-Stack LLM Providers
OpenAI (GPT-4) Anthropic (Claude 3) Cohere AI21 Labs Mistral AI
Open Source Models & Frameworks
Meta (Llama 3) Hugging Face Stability AI DeepSeek MosaicML
Training & Fine-Tuning
Weights & Biases Anyscale Scale AI Labelbox Snorkel
Enterprise Applications
General Productivity
Microsoft Copilot Google Workspace AI Notion AI Jasper Writer
Code & Development
GitHub Copilot Replit Tabnine Codeium Sourcegraph
Sales & Customer Support
Salesforce Einstein Drift Intercom AI Gong Chorus.ai
Marketing & Content
Typeface Regie.ai Persado Moveworks Synthesia
Data Analysis & Business Intelligence
Tableau AI Power BI ThoughtSpot Dataiku H2O.ai
Industry Verticals
Healthcare
Tempus Insilico Medicine PathAI Paige.AI Owkin
Financial Services
Upstart Adept AI Alphasense Kensho Numerai
Legal
Harvey Casetext Ironclad Lexion Clearbrief
Media & Entertainment
Runway Midjourney Descript ElevenLabs Suno
Manufacturing & Design
Autodesk Siemens AI Cognite Augury Veo Robotics
Consumer Applications
Chatbots & Assistants
ChatGPT (59.7% market share) Microsoft Copilot (14.4%) Google Gemini (13.5%) Perplexity (6.2%) Claude AI (3.2%)
Image Generation
DALL-E Midjourney Stable Diffusion Leonardo.AI Ideogram
Video Generation
Runway Gen-2 Pika Labs Synthesia D-ID HeyGen
Audio & Music
ElevenLabs Suno Udio Resemble AI Descript
Market Trends
The generative AI landscape continues to evolve rapidly, with key trends including:
Consolidation among AI providers, with major platform companies integrating smaller specialized AI firms Increasing focus on AI governance and regulation, with the EU leading through its AI Act Shift from experimentation to ROI focus as companies seek to demonstrate value from investments Rise of AI agents capable of autonomous action, with 25% of enterprises expected to deploy them by 2025
Data Sources
This landscape is based on comprehensive research from multiple sources including:
IoT Analytics: "Generative AI Market Report 2025–2030" (January 2025) FirstPageSage: "Top Generative AI Chatbots by Market Share" (March 2025) Research and Markets: "Generative AI: Global Markets" (January 2025) TechTarget: "The future of generative AI: 10 trends to follow in 2025" (February 2025)
Generative AI Landscape 2025
Overview
This visualization presents a comprehensive mapping of the generative AI ecosystem as of 2025, categorizing key players across the value chain from infrastructure to applications.
Market Context
The generative AI market has experienced explosive growth since the introduction of ChatGPT in late 2022, reaching approximately
Infrastructure Layer
At the foundation of the generative AI ecosystem lies the infrastructure that powers model development and deployment.
Hardware Providers
NVIDIA (92% GPU market share) AMD Intel Google TPU
Cloud Service Providers
Microsoft Azure AWS Google Cloud Oracle Cloud
Data Storage & Processing
Snowflake Databricks MongoDB Pinecone Weaviate
Foundation Models & Development
Full-Stack LLM Providers
OpenAI (GPT-4) Anthropic (Claude 3) Cohere AI21 Labs Mistral AI
Open Source Models & Frameworks
Meta (Llama 3) Hugging Face Stability AI DeepSeek MosaicML
Training & Fine-Tuning
Weights & Biases Anyscale Scale AI Labelbox Snorkel
Enterprise Applications
General Productivity
Microsoft Copilot Google Workspace AI Notion AI Jasper Writer
Code & Development
GitHub Copilot Replit Tabnine Codeium Sourcegraph
Sales & Customer Support
Salesforce Einstein Drift Intercom AI Gong Chorus.ai
Marketing & Content
Typeface Regie.ai Persado Moveworks Synthesia
Data Analysis & Business Intelligence
Tableau AI Power BI ThoughtSpot Dataiku H2O.ai
Industry Verticals
Healthcare
Tempus Insilico Medicine PathAI Paige.AI Owkin
Financial Services
Upstart Adept AI Alphasense Kensho Numerai
Legal
Harvey Casetext Ironclad Lexion Clearbrief
Media & Entertainment
Runway Midjourney Descript ElevenLabs Suno
Manufacturing & Design
Autodesk Siemens AI Cognite Augury Veo Robotics
Consumer Applications
Chatbots & Assistants
ChatGPT (59.7% market share) Microsoft Copilot (14.4%) Google Gemini (13.5%) Perplexity (6.2%) Claude AI (3.2%)
Image Generation
DALL-E Midjourney Stable Diffusion Leonardo.AI Ideogram
Video Generation
Runway Gen-2 Pika Labs Synthesia D-ID HeyGen
Audio & Music
ElevenLabs Suno Udio Resemble AI Descript
Market Trends
The generative AI landscape continues to evolve rapidly, with key trends including:
Consolidation among AI providers, with major platform companies integrating smaller specialized AI firms Increasing focus on AI governance and regulation, with the EU leading through its AI Act Shift from experimentation to ROI focus as companies seek to demonstrate value from investments Rise of AI agents capable of autonomous action, with 25% of enterprises expected to deploy them by 2025
Data Sources
This landscape is based on comprehensive research from multiple sources including:
IoT Analytics: "Generative AI Market Report 2025–2030" (January 2025) FirstPageSage: "Top Generative AI Chatbots by Market Share" (March 2025) Research and Markets: "Generative AI: Global Markets" (January 2025) TechTarget: "The future of generative AI: 10 trends to follow in 2025" (February 2025)
Summary
Overall, the experience with Manus is pretty good, better than some products I've tried before, which may be related to the fact that they accumulated a lot of real user needs for AI when working on Monica. Because other AI Agents on the market were not practical, I also wrote some Shortcuts calling the ChatGPT API myself to handle daily tasks, but Manus feels more convenient and efficient.
I've experienced many CUA-related products before, such as:
OpenAI releases new features: Operator and CUA, allowing AI to handle your web-based tasks Anthropic's Claude can directly operate a computer Tencent's AppAgent: A multi-modal intelligent agent that automatically interacts with applications
Compared to Manus, the ones mentioned above are more like demos rather than mature and usable products.
Although some people question whether Manus might have a marketing aspect, I personally believe:
On one hand, leveraging hot topics to gain traffic is not a bad thing,Marketing itself is a reflection of a team's capabilities.。
On the other hand, as long as the team can effectively take advantage of this wave of attention to iterate quickly, the growth rate will definitely be much faster than relying solely on "working in isolation."
I've seen people in various groups question technology packaging and prompt engineering. From an investor's perspective, this issue is more important because the depth of the technology directly determines the product's competitive barriers and long-term value. However, from a user’s point of view, this actually doesn't matter much. What users truly care about is whether the product can solve their problems, if it's convenient to use, and if the results are noticeable—they don’t pay too much attention to whether the underlying technology is packaged or not. Moreover, as the user base grows and commercialization capabilities improve, this can, in turn, continuously enhance the technical competitiveness.
Seeing excellence, we should aspire to it—there's certainly a lot for us to learn here!